Journal of Intelligent & Fuzzy Systems - Volume 45, issue 6

Authors: Srivastava, Stuti | Bansal, Richa | Thapar, Antika

Article Type: Research Article

Abstract: Bandwidth consecutive multicoloring problem is also known as a b-coloring problem. Let G  = (V , E ) be a graph where V is the set of vertices and E is the set of edges. Let each vertex v of V has a positive integer weight b  (v ) and each edge (v , w ) of E has a non-negative integer weight b  (v , w ). A bandwidth consecutive multicoloring of a graph is a problem of assigning b  (v ) consecutive positive integers to each vertex v of V in such …a manner that the difference between all the integers of vertex v and all the integers of vertex w is greater than b  (v , w ). The maximum integer assigned in this coloring is called the span of the coloring. The b-coloring is the problem of minimizing this span. No metaheuristic is proposed for general graphs so far for this problem till date as it is strongly NP-hard. In this paper, we proposed three heuristics for the problem including a greedy randomized adaptive search procedure (GRASP). The efficiency of these algorithms is tested on benchmark graphs and their performance is compared among themselves. Experimental results showed that among all three proposed heuristics, GRASP performed well for the given problem. Show more

Keywords: Graph theory, bandwidth coloring, greedy coloring, GRASP

DOI: 10.3233/JIFS-224242

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 9991-10002, 2023

Authors: Weng, Zhi | Liu, Ke | Zheng, Zhiqiang

Article Type: Research Article

Abstract: The detection and identification of individual cattle plays an integral role in precision feeding and insurance claims, among others. Most current research is based on high-performance computing devices, which limits the application of deep learning techniques to mobile terminals. To this end, in this paper, we propose a channel-pruned YOLOv5 network-based method for cattle face detection on mobile terminals, referred to as NS-YOLO. First, the original model is sparsely trained and a sparse regularization penalty term is applied to the BN layers, then the corresponding mask values are labeled according to different weight thresholds, and the channels are pruned with …global thresholds. Second, the detection precision is recovered by fine-tuning the model. Finally, the NCNN forward inference framework is used to quantize the model and an Android-based cattle face detection application is developed. Experimental results show that the model size, number of parameters and FLOPs are reduced by 86.10%, 88.19% and 63.25%, respectively, and the inference time is reduced by 35.53% compared to the original model, while mAP0.5 is reduced by only 1.6%. In particular, the 16-bit quantized model reduces the model size by 93.97% and the inference time by 34.97% compared to the original model on the mobile side. The results show that the proposed method can be easily deployed in resource-constrained mobile devices and has great advantages in practical engineering applications. Show more

Keywords: Cattle face detection, channel pruning, YOLOv5, model quantization, mobile deployment

DOI: 10.3233/JIFS-232213

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10003-10020, 2023

Authors: Tang, Bin | Xie, Kai | Tao, Wenbin | Liu, Zhenyu | Zhu, Chuanqi | Zhao, Neng | Wang, Yiyang

Article Type: Research Article

Abstract: In order to improve bearing capacity of rockbolts in deep-buried coal mine roadways, orthogonal tests were conducted to study influencing factors of rockbolt anchoring effect. Wavelet neural network model was introduced to predict the pull-out force of rockbolt. The activation and output functions of the wavelet neural network were improved, and the scaling and translation parameters were also modified by using the gradient descent method. These improvements enhanced the approximation rate of the wavelet neural network model, and solve the problem that the wavelet transform method is monotonous and difficult to adapt to the complex and variable engineering conditions. Research …results illustrated that The value of the ultimate pull-out force is positively correlated with the strength of the specimen and pre-tension value of the specimen. According to the test results, the coal mine roadway support scheme was optimized, and the high prestress full-length anchoring rockbolt support technology was proposed. The effectiveness of research was verified through the engineering applications and in-situ monitoring results. Show more

Keywords: Rockbolt, improved Wavelet Neural Network, high prestress, pull-out test, field performance

DOI: 10.3233/JIFS-232435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10021-10032, 2023

Authors: Li, Jing | Li, Chengyu | Meng, Lusha

Article Type: Research Article

Abstract: Global warming caused by excessive emissions of carbon dioxide (CO2 ) has become a hot topic globally in today’s society, and optimizing carbon emission performance (CEP) is an effective way to alleviate CO2 emissions. Many studies have explored CEP at the global, national, provincial and sector levels. However, due to the difficulty in obtaining energy consumption data, there is a lack of studies at the urban agglomeration and city levels. Taking the urban agglomeration dimension as the starting point, this paper constructs an improved epsilon-based measure (EBM) model to measure the CEP of the Yellow River Basin. A spatial …data analysis model was introduced to explore the regional spatial characteristics of CEP. The newly developed spatial statistical model was used to study the driving factors of CEP. The results showed that: (1) The overall CEP of the Yellow River Basin was relatively high, showing an upward trend of volatility. There were significant differences between the seven urban agglomerations and 69 cities. (2) The CEP of the Yellow River Basin showed a trend of spatial agglomeration. The urban agglomerations of the eastern region showed a low-value agglomeration phenomenon, and the urban agglomerations of the central and western regions showed a trend of high-value agglomeration. (3) Economic development level (PGGDP), technological progress (TP), industrialization level (IND) and human capital (HC) can play a positive role in promoting the improvement in CEP, and population structure (PD) and energy structure (ES) can play a negative role in promoting the improvement in CEP. Industrial agglomeration (IA) and CEP show a “U"-shaped relationship that first inhibits and then promotes. In addition, foreign direct investment (FDI), IND, and HC have significant spatial spillover effects on neighboring cities. Show more

Keywords: Yellow River Basin, urban agglomeration, carbon emission performance, spatial Durbin model, spatial agglomeration

DOI: 10.3233/JIFS-233246

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10033-10052, 2023

Authors: Shu, Mingming | Liu, Xiaoyu | Zhou, Hongming

Article Type: Research Article

Abstract: In order to better realize the effective display of painting art, this paper puts forward an interactive modeling method of structural sense of painting art communication from the perspective of media integration. From the perspective of comprehensive media, the painting art is spread and displayed, and the interactive evaluation index of painting art communication structure sense is constructed, and the interactive behavior evaluation model of painting art communication structure sense is constructed to realize the interactive modeling of communication structure sense. The experimental results show that from the perspective of integrating media, the somatosensory interaction mode of the communication structure …of painting art is highly practical in the practical application process, which meets the research requirements and can realize the effective display of painting art in a modified way. Show more

Keywords: Integrated media perspective, painting art, somatosensory interaction

DOI: 10.3233/JIFS-234284

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10053-10062, 2023

Authors: Zhang, Hu | Bai, Ping | Li, Ru

Article Type: Research Article

Abstract: Short text classification task is a special kind of text classification task in that the text to be classified is generally short, typically generating a sparse text representation that lacks rich semantic information. Given this shortcoming, scholars worldwide have explored improved short text classification methods based on deep learning. However, existing methods cannot effectively use concept knowledge and long-distance word dependencies. Therefore, based on graph neural networks from the perspective of text composition, we propose concept and dependencies enhanced graph convolutional networks for short text classification. First, the co-occurrence relationship between words is obtained by sliding window, the inclusion relationship …between documents and words is obtained by TF-IDF, long-distance word dependencies is obtained by Stanford CoreNLP, and the association relationship between concepts in the concept graph with entities in the text is obtained through Microsoft Concept Graph. Then, a text graph is constructed for an entire text corpus based on the four relationships. Finally, the text graph is input into graph convolutional neural networks, and the category of each document node is predicted after two layers of convolution. Experimental results demonstrate that our proposed method overall best on multiple classical English text classification datasets. Show more

Keywords: Short text classification, Knowledge graph, Graph convolutional neural networks, Long-distance dependency, Building graph for text

DOI: 10.3233/JIFS-222407

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10063-10075, 2023

Authors: Guo, Peng | Wang, Xiaonan | Zhang, Duo

Article Type: Research Article

Abstract: Punishment promotes cooperation among selfish agents. Unlike previous studies, we propose a new supervision (heterogeneous preference supervision, HPS) mechanism based on the original random supervision (ORS) mechanism considering regulators’ limited supervision ability and agents’ heterogeneous preferences. The concepts of exemption list capacity, observation period, and removal time are introduced as the variables under the HPS mechanism. A public goods game model is built to verify the supervision effects under the ORS and HPS mechanisms. The simulation results show that the HPS mechanism can promote cooperation more than the ORS mechanism. Increasing the exemption list capacity can make regulators pay more …attention to defectors and improve the cooperation level. Setting a relatively moderate observation period benefits a better supervision effect, while a too-small or too-large observation period leads to the collapse of cooperation. Shortening the removal time can increase the updating speed of the exemption list and enhance the role of the exemption list, resulting in improving the fraction of cooperators. Show more

Keywords: Public goods game, supervision mechanism, supervision ability, heterogeneous preference, exemption list

DOI: 10.3233/JIFS-230775

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10077-10088, 2023

Authors: Bharathi, J. | Nandhini, S.

Article Type: Research Article

Abstract: This paper explores the behaviour of a Bulk Arrival Retrial Queue Model (BARQ) with two phases of service under the Bernoulli Vacation schedule and Breakdown (BVSB). Each batch of customers arriving the system finds if the server is available, instantly utilizes the service. If the server is busy, under breakdown, or taking a vacation, then the customers enter into the orbit. After completing both service stages, the server will either take a vacation with probability p or wait until the next customer arrives with probability 1 - p or q . Our approach considers the nature of the customer as …balking and also takes into account the breakdown of server, which may occur instantaneously during any stage of service. Significant performance measures have been derived and presented. A numerical study of the proposed model is carried out using MATLAB and results were reported. Show more

Keywords: Retrial Queues, two types of service, Bernoulli Vacation, steady-state, Fortuitous Breakdown, impatient customers

DOI: 10.3233/JIFS-231195

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10089-10098, 2023

Authors: Thilagavathy, A. | Mohanaselvi, S.

Article Type: Research Article

Abstract: Consolidating cubical fuzzy numbers (CFNs) is essential in an uncertain decision-making process. This study focuses on creating innovative cubical fuzzy aggregation operators based on the newly proposed Einstein operational laws, utilizing the Bonferroni mean function to capture the interrelationships among the aggregated CFNs. The first contribution of this paper is introducing a novel cubical fuzzy Einstein Bonferroni mean averaging operator. Building upon this operator, we extend our research to develop cubical fuzzy Einstein Bonferroni mean weighted, ordered weighted, and hybrid averaging operators, taking into account the weights of the aggregated CFNs. To ensure their effectiveness, we thoroughly investigate the desirable …properties of these proposed operators. Furthermore, we leverage the introduced operators to establish a new approach known as the cubical fuzzy linear assignment method, which proves valuable in resolving multiple criteria group decision-making problems. As a practical demonstration of the method’s utility, we apply it to address a real-life challenge: identifying the optimal location for constructing a wind power plant under a cubical fuzzy environment. To validate the effectiveness of our approach, we compare its results with those obtained using existing methods from the literature. Additionally, we conduct a statistical analysis to visualize the correlative conjunction between the ranking outcomes obtained by different operators Show more

Keywords: Cubical fuzzy set, Einstein operational laws, Bonferroni mean, averaging aggregation operators, linear assignment method, wind power plant location selection

DOI: 10.3233/JIFS-232252

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10099-10125, 2023

Authors: Guo, Yijian | Sun, Kaiqiong | Luo, Gang | Wang, Meng

Article Type: Research Article

Abstract: Leaf segmentation is crucial for plant recognition, especially for tree species identification. In natural environments, leaf segmentation can be very challenging due to the lack of prior information about leaves and the variability of backgrounds. In typical applications, supervised algorithms often require pixel-level annotation of regions, which can be labour-intensive and limited to identifying plant species using pre-labelled samples. On the other hand, traditional unsupervised image segmentation algorithms require specialised parameter tuning for leaf images to achieve optimal results. Therefore, this paper proposes an unsupervised leaf segmentation method that combines mutual information with neural networks to better generalise to unknown …samples and adapt to variations in leaf shape and appearance to distinguish and identify different tree species. First, a model combining a Variational Autoencoder (VAE) and a segmentation network is used as a pre-segmenter to obtain dynamic masks. Secondly, the dynamic masks are combined with the segmentation masks generated by the mask generator module to construct the initial mask. Then, the patcher module uses the Mutual Information Minimum (MIM) loss as an optimisation objective to reconstruct independent regions based on this initial mask. The process of obtaining dynamic masks through pre-segmentation is unsupervised, and the entire experimental process does not involve any label information. The experimental method was performed on tree leaf images with a naturally complex background using the publicly available Pl@ntLeaves dataset. The results of the experiment showed that compared to existing excellent methods on this dataset, the IoU (Intersection over Union) index increased by 3.9%. Show more

Keywords: Leaf extraction, deep learning, unsupervised image segmentation, mutual information, VAE

DOI: 10.3233/JIFS-232696

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 10127-10139, 2023